A Lightweight Fault-Detection Scheme for Barrett Modular Multiplication Using Multiple Conditional Reduction Paths
- URL: http://arxiv.org/abs/2608.10736v1
- Date: Tue, 11 Aug 2026 09:55:24 GMT
- Title: A Lightweight Fault-Detection Scheme for Barrett Modular Multiplication Using Multiple Conditional Reduction Paths
- Abstract summary: Polynomial multiplication is the most resource-, time-, and energy-critical operation in lattice-based Post-Quantum Cryptography (PQC) schemes.<n>Side-Channel Attacks (SCAs) and Hardware Trojans may introduce intentional faults, while aging and various other factors can cause unintentional faults.<n>In this paper, we employ a Statistical Reduction Monitoring (SRM) method to protect the BM M unit against such adversarial conditions.
- Score: 2.3717455032900547
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: Polynomial multiplication is the most resource-, time-, and energy-critical operation in lattice-based Post-Quantum Cryptography (PQC) and Fully Homomorphic Encryption (FHE) schemes. Lattice-based PQC schemes such as Kyber and Dilithium have already been standardized, while lattice- based FHE schemes such as BGV, BFV, and CKKS are widely recognized as leading candidate in FHE area. Barrett Modular Multiplication (BMM) for polynomial multiplication is widely adopted in PQC and FHE hardware accelerators due to its hardware friendly nature and efficient modular reduction capabilities. However, Side-Channel Attacks (SCAs) and Hardware Trojans may introduce intentional faults, while aging and various other factors can cause unintentional faults. These faults may target the BM M unit, one of the most critical components of PQC and FHE infrastructures, potentially leading to information leakage and compromising system security. In this paper, we employ a Statistical Reduction Monitoring (SRM) method to protect the BM M unit against such adversarial conditions. The proposed approach incurs minimal hardware overhead while providing efficient detection of both random and bur
Related papers
- Distributed Motion Planning with Safety Guarantees for Self-Reconfiguring Robotic Boats [76.98547580312116]
This paper proposes a hybrid framework that combines distributed Model Predictive Control (MPC) with Control Barrier Functions (CBFs)<n>To ensure safety in real time, distributed CBF-based filters are applied to enforce inter-agent avoidance.
arXiv Detail & Related papers (2026-07-22T16:37:05Z) - LFQ: Logit-aware Final-block Quantization for Boosting the Generation Quality of Low-Bit Quantized LLMs [52.1276403258812]
We introduce Logit-aware Final-block Quantization (LFQ), a simple yet effective enhancement to block-wise PTQ.<n>LFQ consistently improves the accuracy of complex generation tasks over state-of-the-art block-wise PTQ.
arXiv Detail & Related papers (2026-05-28T11:02:23Z) - Trojan-Resilient NTT: Protecting Against Control Flow and Timing Faults on Reconfigurable Platforms [2.5909615773091526]
Number Theoretic Transform (NTT) is the most essential component for multiplications used in lattice-based Post-Quantum Cryptography (PQC) algorithms.<n>Side-channel attacks (SCA) and hardware vulnerabilities in the form of hardware Trojans may alter control signals to disrupt the circuit's control flow.<n>We present a secure NTT architecture capable of detecting unconventional delays, control-flow disruptions, and SASCA.
arXiv Detail & Related papers (2026-01-30T10:33:39Z) - Composable Verification in the Circuit-Model via Magic-Blindness [0.0]
We introduce a family of noise robust, composable and efficient verification protocols for Clifford + MSI circuits.<n>Our technique is based on a refined notion of blindness, called magic-blindness, which hides only the injected magic states.<n>As a result, circuit-based quantum verification attains the same level of security and robustness previously known only in MBQC.
arXiv Detail & Related papers (2026-01-12T00:30:24Z) - Lightweight Fault Detection Architecture for NTT on FPGA [0.8793721044482612]
Post-Quantum Cryptographic (PQC) algorithms are mathematically secure and resistant to quantum attacks.<n>They can still leak sensitive information in hardware implementations due to natural faults or intentional fault injections.<n>This research proposes a lightweight, efficient, recomputation-based fault detection module.
arXiv Detail & Related papers (2025-08-05T04:23:50Z) - RTL Interconnect Obfuscation By Polymorphic Switch Boxes For Secure Hardware Generation [0.0]
We present an interconnect obfuscation scheme at the Register-Transfer Level (RTL) using Switch Boxes (SBs) constructed of Polymorphic Transistors.
A polymorphic SB can be designed using the same transistor count as its Complementary-Metal-Oxide-Semiconductor based counterpart.
arXiv Detail & Related papers (2024-04-11T01:42:01Z) - Deep Learning Assisted Multiuser MIMO Load Modulated Systems for
Enhanced Downlink mmWave Communications [68.96633803796003]
This paper is focused on multiuser load modulation arrays (MU-LMAs) which are attractive due to their low system complexity and reduced cost for millimeter wave (mmWave) multi-input multi-output (MIMO) systems.
The existing precoding algorithm for downlink MU-LMA relies on a sub-array structured (SAS) transmitter which may suffer from decreased degrees of freedom and complex system configuration.
In this paper, we conceive an MU-LMA system employing a full-array structured (FAS) transmitter and propose two algorithms accordingly.
arXiv Detail & Related papers (2023-11-08T08:54:56Z) - Towards Semantic Communication Protocols: A Probabilistic Logic
Perspective [69.68769942563812]
We propose a semantic protocol model (SPM) constructed by transforming an NPM into an interpretable symbolic graph written in the probabilistic logic programming language (ProbLog)
By leveraging its interpretability and memory-efficiency, we demonstrate several applications such as SPM reconfiguration for collision-avoidance.
arXiv Detail & Related papers (2022-07-08T14:19:36Z) - Modular Deep Reinforcement Learning for Continuous Motion Planning with
Temporal Logic [59.94347858883343]
This paper investigates the motion planning of autonomous dynamical systems modeled by Markov decision processes (MDP)
The novelty is to design an embedded product MDP (EP-MDP) between the LDGBA and the MDP.
The proposed LDGBA-based reward shaping and discounting schemes for the model-free reinforcement learning (RL) only depend on the EP-MDP states.
arXiv Detail & Related papers (2021-02-24T01:11:25Z) - Covert Model Poisoning Against Federated Learning: Algorithm Design and
Optimization [76.51980153902774]
Federated learning (FL) is vulnerable to external attacks on FL models during parameters transmissions.
In this paper, we propose effective MP algorithms to combat state-of-the-art defensive aggregation mechanisms.
Our experimental results demonstrate that the proposed CMP algorithms are effective and substantially outperform existing attack mechanisms.
arXiv Detail & Related papers (2021-01-28T03:28:18Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.